10 Step Roadmap to Become an Expert Data Engineer with Projects

Are you starting from scratch and want to become a data engineer in 2025? In this video, I’ll walk you through a complete 10-step roadmap that takes you from absolute beginner to job-ready expert, with real-world, cloud-based projects across Azure, AWS, and GCP. ✅ Whether you're transitioning careers, just finished a bootcamp, or looking to level up—this guide is packed with everything you need: ✅ Tools (Airflow, dbt, PySpark, Azure Data Factory, Terraform) ✅ Hands-on projects (batch & streaming pipelines) ✅ Portfolio-building tips ✅ DevOps & infrastructure best practices ✅ End-to-end architecture examples 🎯 Cloud Projects Included: ✅ Azure: Event Hubs → Databricks → Synapse → Power BI ✅ AWS: S3 → Glue → Redshift ✅ GCP: Pub/Sub → Dataflow → BigQuery 🛠 Topics Covered: ✅ Python & SQL Foundations ✅ Relational & NoSQL Databases ✅ Data Warehousing ✅ ETL & ELT Pipelines ✅ Airflow & Orchestration ✅ Batch Data Processing (Spark) ✅ Stream Processing (Kafka, Event Hubs) ✅ Multi-cloud Architecture ✅ Infrastructure as Code (Terraform, Docker) ✅ Final Capstone & Job Prep 📌 Timestamps 0:00 Introduction 2:05 Step 1: Programming & SQL 6:05 Step 2: Data Modeling and Relational Databases 12:30 Step 3: Data Warehouse & NoSQL 15:30 Data pipelines 19:35 Workflows Orchestration 22:09 Batch processing 24:24 Stream Processing 27:10 Cloud 29:10 DevOps 31:37 Capstone Projects and Portfolio 35:06 Final Advice 👍 Like the video? 🔔 Subscribe for more data engineering content 💬 Drop your questions or roadmap progress in the comments!